Dense embedding have continuous numeric values. i.e after decimal point values will be present. Chunk will be converted to embeddings, each embedding point will have number like [0.3455566 ,0.6777779, ...]. Generated vectors will be plotted in a space called latent space. Discrete values like 0 won't be present.
Sparse embedding will mostly have values like 0. Rather than semantic meaning, it considers frequency or importance of words in a text.
Ex: one hot encoding
Models for Dense embedding
1. LLM
